This invention relates to image processing and more particularly to encoding of images in a manner that would permit transmission and/or storage of image information in the most efficient manner.
With the advent of wideband electronic transmission capabilities (such as the AT&T ISDN), the wide spread installation of personal computers, and the ever increasing power of work stations, we are entering a new area where the manipulation of large amounts of digital pictorial information has become feasible. To simplify communication of pictorial data, a serious international effort is underway to standardize on algorithms for compression of both still pictures and active video (ISO/CCITT).
Different compression methods have evolved in the art as understanding of pictorial data increased and theoretical advances were made. Differential Pulse Code Modulation (DPCM) and bit-plane coding were among the early methods used, and they achieved compression factors of up to 4-6 by trading image quality for lower bit rate. Pictures with higher quality than obtainable with DPCM, coded with only one bit per pixel, can now be obtained with a number of methods, such as the Adaptive Discrete Cosine Transform (ADCT) described by W. H. Chen and C. H. Smith, in "Adaptive Coding of Monochrome and Color Images", IEEE Trans. Comm., vol. COM-25, pp. 1285-1292, November 1977. In an ADCT coding system, the image is decomposed into blocks, generally eight by eight, and for each of the blocks a DCT (Discrete Cosine Transform) is carried out. The compression is obtained by quantization of the DCT coefficients with variable thresholds, optimized for the human visual acumen, followed by variable word length encoding.
In the context of speech, compression has been achieved by the use of sub-band coding techniques, as described, for example, by R. E. Crochiere, et al. "Digital Coding of Speech in Sub-Bands," Bell. Syst. Tech. J., vol. 55, pp. 1069-1085, October 1976. The speech sub-band coding technique consists of decomposing the signal into separate frequency bands and coding the outputs of the different bands according to their energy levels.
Borrowing from the speech area, sub-band coding of images have been introduced to picture coding. One arrangement was proposed by J. W. Woods and S. D O'Neil, in "Sub-Band Coding of Images", IEEE ASSP, vol. ASSP-34 No. 5, October 1986, pp. 1278-1288. The arrangement proposed by Woods at al. includes a filter bank, that divides the image signal into bands of different frequency content, and the signal of each filter output is compressed via DPCM. The compressed signals are then transmitted to a receiver where the process is reversed. Specifically, each signal is DPCM decoded and then up-sampled, filtered, and combined with the other filtered signals to recover the original image.
H. Gharavi and A. Tabataba in "Sub-Band Coding of Images Using Two-Dimensional Quadrature Mirror Filtering," Proc. SPIE, vol. 707, pp. 51-61, September 1986, use long complex quadrature mirror filters to obtain a number of frequency band signals. The "low-low" band is DPCM coded using a two-dimensional DPCM codec. A dead-zone quantizer is used for the other bands, followed by PCM coding.
Other sub-band coding schemes such as proposed by P. H. Westerink, J. W. Woods and D. E. Boekee in Proc. of Seventh Benelux Information Theory Symposium, pp. 143-150, 1986, apply vector-quantization techniques to code the filter bank outputs.
Up to now, however, sub-band coding techniques did not achieve the image quality and compression ratios obtained with other methods. This is mainly due to the interband correlation that is present in the signal, but that is not removed by the prior art techniques. Another major problem with some of the sub-band coding approaches is the cost of the computations of long complex filters.